IMU Preintegration for Multi-Robot Systems in the Presence of Bias and Communication Constraints

TL;DR

This paper extends IMU preintegration methods for multi-robot systems to account for sensor biases and communication constraints, enhancing the accuracy and robustness of relative pose estimation.

Contribution

It introduces a way to incorporate IMU biases into the existing preintegration framework while preserving its differential Sylvester equation form.

Findings

IMU bias incorporation improves pose estimation accuracy

Framework maintains computational efficiency with biases included

Enhanced robustness in multi-robot relative localization

Abstract

This document is in supplement to the paper titled "Multi-Robot Relative Pose Estimation and IMU Preintegration Using Passive UWB Transceivers", available at [1]. The purpose of this document is to show how IMU biases can be incorporated into the framework presented in [1], while maintaining the differential Sylvester equation form of the process model.